Notes on technology.
Partner at zaka.vc, investing early in health and industrial technologies. Having seen and read a great deal, and understood rather less of it, I am using this page to organise what stayed.
Writing
·zaka.vc·clinical trials
We now design more drugs than we can test
Discovery got much better at producing candidates and the step that tests them did not. Nearly four in ten adjuvant phase III oncology trials finish with less statistical power than their own design called for, and two thirds of trial starts now come from sponsors running their first or second study. The scarce input stopped being the molecule. It is a credible answer about one, and the CRO selling you the trial has no reason to hand you that.
Read on zaka.vc →·zaka.vc·drug discovery
Nobody at a frontier lab is working on your disease
Frontier labs walking into drug discovery looks like an extinction event for seed-stage biotech. Alphabet ran the same experiment for twelve years across Calico, Verily and Isomorphic, and came up empty. Capital, patience and a Nobel-winning model were never the scarce inputs. Proprietary data and a program someone sees through still are.
Read on zaka.vc →·zaka.vc·drug discovery
The moat decides whether you can play. The asset decides whether you get paid.
Discovery is priced before anyone knows the molecule works. Schrödinger co-discovered the compound Nimbus sold to Takeda for $4 billion and took home $147 million. A data moat tells you nobody can copy you. It says nothing about who pays you, and in target discovery the gap between those two is the whole business.
Read on zaka.vc →·zaka.vc·drug discovery
In AI drug discovery, the model was never the moat
The question is no longer whether AI can design drugs but who keeps an edge once the frontier labs commoditize the model layer. The one test that survives: does a company manufacture biological data nobody else can. Archetype and business-model labels tell you little; data ownership tells you everything.
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